Causal Inference in a Multidimensional Latent Mediator Model for the Relationship Between Predictive Cues and Neural Activity in the Brain's Pain Processing Network

• Activity Number: 469
• Type: Invited
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Social Statistics Section
• Author(s): Michael Sobel* and Martin A. Lindquist
• Companies: Columbia University and The Johns Hopkins University
• Keywords: causal inference ; mediation ; latent variables ; fMRI

Abstract

Neuroscientists have identified a network (PPN) of brain regions involved in pain processing. An important question is if this is modulated by subjects' expectations, and if so, how this works. We analyze data from a study of 19 subjects observed on multiple trials. In each trial, a subject is told he/she will receive a high (H) or (L) low level of a pain inducing thermal stimulus. The H (L) cue is then followed by either an H or medium (M) (L or M) stimulus. The stimulus was then applied, after which the subject reported their level of pain. During the trial, the blood oxygenation level dependent (BOLD) responses from approximately 100,000 voxels are observed. We analyze these responses and compare the latent amplitudes under the H cue, M stimulus condition and the L cue, M stimulus condition, concluding that the cue modulates the response to the stimulus. We then construct a causal model for how the cue mediates the relationship between the amplitudes and the thermal stimulus.